CMAC based iterative learning control of robot manipulators
- Resource Type
- Conference
- Authors
- Tae-Young Kuc; Kwanghee Nam
- Source
- Proceedings of the 28th IEEE Conference on Decision and Control, Decision and Control, 1989., Proceedings of the 28th IEEE Conference on. :2613-2618 vol.3 1989
- Subject
- Robotics and Control Systems
Computing and Processing
Robot control
Manipulator dynamics
Robot kinematics
Motion control
Torque control
Error correction
Convergence
Feedback
Robot motion
Iterative methods
- Language
An iterative learning control scheme is presented. It incorporates a version of the cerebellar model articulation controller (CMAC) memory for the torque sequence generation. A learning rule is constructed by utilizing a gradient descent algorithm, and a map which updates old data stored in a distributed form is defined. It is shown that the training factor should be less than two for error convergence in the case of high-gain feedback.ETX